In many medical treatments, such as chemotherapy for cancer patients and Interferon treatment for hepatitis C, administration of the treatment to a group of individuals in the population suffering from an illness can result in inconsistent results in which some of the individuals respond to the treatment while others do not. When the variability in the response has a genetic basis, a genetic analysis, such as microarray technology may be utilized to characterize genetically those individuals that responded to the treatment and those that did not in order to be able to predict which people suffering from the illness would respond to the treatment and which would not.
For the vast majority of the genes in the genome, the gene expression level in the individuals that respond to the treatment is not significantly different from those that do not. Only a very small number of genes in the genome show a significant difference in their expression level in the two groups. FIG. 1 compares the expression level of 15,000 genes in a group of 11 people suffering from hepatitis C that responded to Interferon treatment with that of a group of 11 people suffering from hepatitis C that did not respond to the treatment. Each circle in the graph of FIG. 1 represents a different gene and has as its x-coordinate the average expression level of the gene among the 11 people responding to the treatment and as its y-coordinate the average expression level of the gene among the 1 not responding to the treatment. As seen in FIG. 1, the vast majority of the circles are on the line y=x 1, indicating that the expression levels of these genes is essentially the same in both groups. Only a very small proportion of the circles deviate significantly from the line y=x. For example, the genes represented by the circles a, b, c and d have an expression level that is significantly higher in the group responding to the treatment in comparison to the group not responding to the treatment.